California Oil Spills

# Read in the CA county data (TIGER shapefile)
ca_counties <- read_sf("ca_counties", layer = "CA_Counties_TIGER2016") %>% 
  clean_names() %>% 
  dplyr::select(name)

# Read in the oil spill data (ds394 shapefile) 
oil_spill <- read_sf("ds394", layer = "ds394") %>% 
  clean_names() 

# Check the projections
st_crs(ca_counties) # WGS84
st_crs(oil_spill) # NAD83

# Transform CA counties to match oil spill data CRS 
ca_counties <- st_transform(ca_counties, st_crs(oil_spill))

st_crs(ca_counties) # NAD83

# Exploratory ggplot
ggplot() + 
  geom_sf(data = ca_counties) +
  geom_sf(data = oil_spill)

# Exploratory interactive map showing the location of oil spill events 
tmap_mode("view")

tm_basemap("Stamen.Watercolor") +
tm_shape(ca_counties) +
  tm_polygons() +
tm_shape(oil_spill) +
  tm_dots()

# Static chloropleth map in which the fill color for each county depends on the count of inland oil spill events by county for the 2008 oil spill data 

ca_oil_spills <- ca_counties %>% 
  st_join(oil_spill) %>% 
  filter(inlandmari == "Inland")

oil_spill_counts <- ca_oil_spills %>% 
  count(name) 

ggplot(data = oil_spill_counts) +
  geom_sf(aes(fill = n), 
          color = "white", 
          size = 0.1) +
    scale_fill_gradientn(colors = c("cadetblue4","orange","violetred")) +
  theme_minimal() +
  labs(fill = "Number of oil \nspill events",
       x = "\nLongitude",
       y = "Latitude\n")

Figure 1: Figure 1. California map of the number of inland oil spill events by county in 2008. Modoc County is not shown as it had zero spill events. Data: California Department of Fish and Wildlife. 2009.

Citations

California Department of Fish and Wildlife, Office of Spill Prevention and Response. 2009. Oil Spill Incident Tracking [ds394]. https://gis.data.ca.gov/datasets/CDFW::oil-spill-incident-tracking-ds394?geometry=-147.064%2C30.769%2C-91.780%2C43.020